Key Points
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MicroRNAs (miRNAs) located in genomic regions amplified in cancers (such as the miR-17–92 cluster) function as oncogenes, whereas miRNAs located in portions of chromosomes deleted in cancers (such as the miR-15a–miR-16-1 cluster) function as tumour suppressors.
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Abnormal expression of miRNAs has been found in both solid and haematopoietic tumours by various genome-wide techniques (including different microarray platforms or bead-based flow cytometry).
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The abnormally expressed miRNAs in human cancers target transcripts of essential protein-coding genes involved in tumorigenesis, such as the Ras oncogenes by let-7 family members, the BCL2 anti-apoptotic gene by the miR-15a–miR-16-1 cluster, the E2F1 transcription factor by the miR-17–92 cluster or the BCL6 anti-apoptotic gene by miR-127.
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MiRNA expression fingerprints correlate with clinical and biological characteristics of tumours, including tissue type, differentiation, aggression and response to therapy.
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The fact that consistent abnormal expression of the precursor miRNA, but not of the correspondent active molecule, is found in various types of cancers, raises the possibility that the 'non-active' part of the miRNA molecule could have 'independent' and as yet unknown functions that could be important in tumorigenesis.
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Germline sequence abnormalities were identified in miRNA genes and transcripts, and in targeted sequences in messenger RNAs that are known to be targets of miRNAs. Furthermore, as each miRNA has many targets, inherited minor variations in miRNA expression could have important consequences for the expression of various protein-coding genes involved in malignant transformation. Therefore, it is tempting to propose that both these phenomenons are involved in familial predisposition to cancer.
Abstract
MicroRNA (miRNA) alterations are involved in the initiation and progression of human cancer. The causes of the widespread differential expression of miRNA genes in malignant compared with normal cells can be explained by the location of these genes in cancer-associated genomic regions, by epigenetic mechanisms and by alterations in the miRNA processing machinery. MiRNA-expression profiling of human tumours has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment. In addition, profiling has been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or that target protein-coding genes involved in cancer.
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Acknowledgements
We want to thank the collaborators and young investigators who contributed to the microRNA work done in our laboratories. C.M.C. is supported by Program Project grants from the US National Cancer Institute, and G.A.C. is supported by a Kimmel Foundation Scholar award and by the CLL Global Research Foundation. We thank M. Negrini and M. Fabbri for their critical reading of the manuscript, and thank A. Cimmino for assistance with the figures. We apologize to many colleagues whose work was not cited owing to space limitations.
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Glossary
- Bead-based flow cytometry
-
A high-throughput microRNA (miRNA)-profiling technique in which individual beads are coupled to miRNA complementary probes and marked with fluorescent tags. After hybridization with size-fractioned RNAs and staining, the beads are analysed using a flow cytometer.
- Hierarchical clustering
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A computational method that groups genes (or samples) into small clusters and then groups these clusters into increasingly higher level clusters. As a result, a dendrogram (that is, a tree) of connectivity emerges.
- Significance analysis of microarrays (SAM)
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A statistical method used in microarray analyses that calculates a score for each gene, and therefore identifies genes that are significantly associated with an outcome variable, such as the type of analysed tissue (normal or cancerous).
- Prediction analysis of microarrays (PAM)
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A statistical technique used in microarray analyses that identifies a subgroup of genes that best characterizes a predefined class, and uses this gene set to predict the class of new samples.
- Richter transformation
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Denotes the development of high-grade non-Hodgkin lymphoma, prolymphocytic leukaemia, Hodgkin disease or acute leukaemia in patients with chronic lymphocytic leukaemia. Current treatments are aggressive, but prognosis is poor.
- Univariate versus multivariate analyses
-
Univariate analysis explores each variable in a data set separately and describes the pattern of response to the variable. It describes each variable on its own. Multivariate statistical analysis describes a collection of procedures that involve the observation and analysis of more than one statistical variable at a time. It describes all variables together.
- Antagomirs
-
A new class of chemically engineered oligonucleotides that efficiently and specifically silence endogenous miRNAs in mice.
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Calin, G., Croce, C. MicroRNA signatures in human cancers. Nat Rev Cancer 6, 857–866 (2006). https://doi.org/10.1038/nrc1997
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DOI: https://doi.org/10.1038/nrc1997
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